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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Advancing flood damage modeling for coastal Alabama residential properties: A multivariable machine learning approach
Mujungu Lawrence Museru, Rouzbeh Nazari, Abolfazl Nazari Giglou, et al.
The Science of The Total Environment (2023) Vol. 907, pp. 167872-167872
Closed Access | Times Cited: 14

Showing 14 citing articles:

Improving flood hazard susceptibility assessment by integrating hydrodynamic modeling with remote sensing and ensemble machine learning
Izhar Ahmad, Rashid Farooq, Muhammad Ashraf, et al.
Natural Hazards (2025)
Open Access | Times Cited: 1
Smarter water quality monitoring in reservoirs using interpretable deep learning models and feature importance analysis
Shabnam Majnooni, Mahmood Fooladi, Mohammad Reza Nikoo, et al.
Journal of Water Process Engineering (2024) Vol. 60, pp. 105187-105187
Closed Access | Times Cited: 12
Enhancing flood risk assessment in urban areas by integrating hydrodynamic models and machine learning techniques
Alireza Khoshkonesh, Rouzbeh Nazari, Mohammad Reza Nikoo, et al.
The Science of The Total Environment (2024) Vol. 952, pp. 175859-175859
Closed Access | Times Cited: 7
Improving Long-Term Flood Forecasting Accuracy Using Ensemble Deep Learning Models and an Attention Mechanism
Marjan Kordani, Mohammad Reza Nikoo, Mahmood Fooladi, et al.
Journal of Hydrologic Engineering (2024) Vol. 29, Iss. 6
Closed Access | Times Cited: 7
Quantification of the Influencing Factors of Stand Productivity of Subtropical Natural Broadleaved Forests in Eastern China Using an Explainable Machine Learning Framework
Qun Du, Chenghao Zhu, Biyong Ji, et al.
Forests (2025) Vol. 16, Iss. 1, pp. 95-95
Open Access
Assessing the impact of climate and land use change on flood vulnerability: a machine learning approach in coastal region of Tamil Nadu, India
Devanantham Abijith, Subbarayan Saravanan, Parthasarathy Kulithalai Shiyam Sundar, et al.
Geoscience Letters (2025) Vol. 12, Iss. 1
Open Access
A critical review of hurricane risk assessment models and predictive frameworks
Sameera Maha Arachchige, Biswajeet Pradhan, Hyuck‐Jin Park
Geoscience Frontiers (2025), pp. 102012-102012
Open Access
Modelling and Mapping Rapid-Onset Coastal Flooding: A Systematic Literature Review
Alice Re, Lorenzo Minola, Alessandro Pezzoli
Water (2025) Vol. 17, Iss. 4, pp. 599-599
Open Access
Can Small Towns Survive Climate Change? Assessing Economic Resilience and Vulnerability Amid Major Storms
Rouzbeh Nazari, Maryam Karimi, Mohammad Reza Nikoo, et al.
Journal of Cleaner Production (2025), pp. 145158-145158
Closed Access
Nonlinear influences of climatic, vegetative, geographic and soil factors on soil water use efficiency of global karst landscapes: Insights from explainable machine learning
Chao Li, Shiqiang Zhang, Yongjian Ding, et al.
The Science of The Total Environment (2025) Vol. 965, pp. 178672-178672
Closed Access
Hydrodynamics-based assessment of flood losses in an urban district under changing environments
Xiaojie Wang, Junqiang Xia, Boliang Dong, et al.
Natural Hazards (2024)
Closed Access | Times Cited: 2
Integrated ensemble learning approach for multi-depth water quality estimation in reservoir environments
Mohammad Sadegh Zare, Mohammad Reza Nikoo, Ghazi Al-Rawas, et al.
Journal of Water Process Engineering (2024) Vol. 66, pp. 105840-105840
Closed Access | Times Cited: 2
Assessment of urban flood susceptibility based on a novel integrated machine learning method
Haidong Yang, Ting Zou, Biyu Liu
Environmental Monitoring and Assessment (2024) Vol. 197, Iss. 1
Closed Access | Times Cited: 1
City scale urban flooding risk assessment using multi-source data and machine learning approach
Wei Qing, Huijin Zhang, Yongqi Chen, et al.
Journal of Hydrology (2024), pp. 132626-132626
Closed Access
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